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fix(profiling): use SGD for pi0/pi05/pi0_fast and free CUDA cache after deterministic forward
Adam optimizer states (exp_avg + exp_avg_sq) require ~16GB extra on top of model params and gradients for 4B parameter models, exceeding the 22GB GPU. SGD has zero optimizer state overhead and profiling only measures forward/backward timing anyway. Also adds torch.cuda.empty_cache() after deterministic forward to release transient memory before the training loop starts. Made-with: Cursor
This commit is contained in:
@@ -63,6 +63,16 @@
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"--policy.use_amp=true",
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"--policy.gradient_checkpointing=true",
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"--batch_size=1",
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"--use_policy_training_preset=false",
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"--optimizer.type=sgd",
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"--optimizer.lr=1e-5",
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"--optimizer.weight_decay=0",
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"--optimizer.grad_clip_norm=1.0",
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"--scheduler.type=cosine_decay_with_warmup",
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"--scheduler.peak_lr=1e-5",
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"--scheduler.decay_lr=1e-6",
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"--scheduler.num_warmup_steps=0",
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"--scheduler.num_decay_steps=12",
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"--rename_map={\"observation.images.front\": \"observation.images.base_0_rgb\", \"observation.images.wrist\": \"observation.images.left_wrist_0_rgb\"}"
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]
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},
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@@ -78,6 +88,16 @@
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"--policy.use_amp=true",
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"--policy.gradient_checkpointing=true",
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"--batch_size=1",
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"--use_policy_training_preset=false",
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"--optimizer.type=sgd",
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"--optimizer.lr=1e-5",
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"--optimizer.weight_decay=0",
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"--optimizer.grad_clip_norm=1.0",
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"--scheduler.type=cosine_decay_with_warmup",
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"--scheduler.peak_lr=1e-5",
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"--scheduler.decay_lr=1e-6",
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"--scheduler.num_warmup_steps=0",
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"--scheduler.num_decay_steps=12",
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"--rename_map={\"observation.images.front\": \"observation.images.base_0_rgb\", \"observation.images.wrist\": \"observation.images.left_wrist_0_rgb\"}"
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]
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},
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@@ -93,6 +113,16 @@
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"--policy.use_amp=true",
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"--policy.gradient_checkpointing=true",
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"--batch_size=1",
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"--use_policy_training_preset=false",
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"--optimizer.type=sgd",
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"--optimizer.lr=1e-5",
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"--optimizer.weight_decay=0",
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"--optimizer.grad_clip_norm=1.0",
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"--scheduler.type=cosine_decay_with_warmup",
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"--scheduler.peak_lr=1e-5",
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"--scheduler.decay_lr=1e-6",
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"--scheduler.num_warmup_steps=0",
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"--scheduler.num_decay_steps=12",
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"--policy.normalization_mapping={\"ACTION\": \"MEAN_STD\", \"STATE\": \"MEAN_STD\", \"VISUAL\": \"IDENTITY\"}",
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"--rename_map={\"observation.images.front\": \"observation.images.base_0_rgb\", \"observation.images.wrist\": \"observation.images.left_wrist_0_rgb\"}"
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]
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